A novel prediction model based on hierarchical characteristic of web site

Internet has developed in a rapid way in the recent 10 years,and the information of web site has also been increasing fast. Predicting web user’s behavior becomes a crucial issue following the purposes like increasing the user’s browsing speed efficiently, decreasing the user’s latency as well as possible and reducing the loading of web server. In this paper, we propose an efficient prediction model, two-level prediction model (TLPM), using a novel aspect of natural hierarchical property from web log data. TLPM can decrease the size of candidate set of web pages and increase the speed of predicting with adequate accuracy. The experiment results prove that TLPM can highly enhance the performance of prediction when the number of web pages is increasing.

Research highlights
► Predicting user behavior by directory information is provided.
► A hierarchical prediction model denoted as TLPM is developed.
► TLMP can highly enhance the performance in the realistic database.